{"title":"Unraveling the Interplay Between Memristive and Magnetoresistive Behaviors in LaCoO<sub>3</sub>/SrTiO<sub>3</sub> Superlattice-Based Neural Synaptic Devices.","authors":"Zeou Yang, Xiaozhong Huang, Yu Liu, Ze Wang, Zhengwei Zhang, Bingyang Ma, Hailong Shang, Lanzhi Wang, Tao Zhu, Xidong Duan, Hailong Hu, Jianling Yue","doi":"10.1002/smtd.202401259","DOIUrl":null,"url":null,"abstract":"<p><p>Memristors and magnetic tunnel junctions are showing great potential in data storage and computing applications. A magnetoelectrically coupled memristor utilizing electron spin and electric field-induced ion migration can facilitate their operation, uncover new phenomena, and expand applications. In this study, devices consisting of Pt/(LaCoO<sub>3</sub>/SrTiO<sub>3</sub>)<sub>n</sub>/LaCoO<sub>3</sub>/Nb:SrTiO<sub>3</sub> (Pt/(LCO/STO)<sub>n</sub>/LCO/NSTO) are engineered using pulsed laser deposition to form the LCO/STO superlattice layer, with Pt and NSTO serving as the top and bottom electrodes, respectively. The results show that both memristive and magnetoresistive properties can coexist without any compromise in performance, and the values of R<sub>OFF</sub>/R<sub>ON</sub> and tunnel magnetoresistance (TMR) ratio are both improved by ≈1000% compared to a single-period heterostructure. Notably, the Pt/(LCO/STO)<sub>5</sub>/LCO/NSTO device demonstrates superior multilevel storage performance, characterized by extended endurance, reliable retention, high R<sub>OFF</sub>/R<sub>ON</sub> ratio, significant TMR ratio, and fundamental synaptic behaviors. Furthermore, density functional theory (DFT) is employed to calculate the changes in oxygen vacancies, affecting the overall energy bands and magnetic moments in the monolayer and multi-periodic structures. Simulations using the handwritten digit recognition classification achieve the highest accuracy of 94.38%. These attributes suggest that the devices hold considerable promise for application in data storage and neuromorphic computing, offering a platform for high-density neural circuits in intelligent electronic devices.</p>","PeriodicalId":229,"journal":{"name":"Small Methods","volume":" ","pages":"e2401259"},"PeriodicalIF":10.7000,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Small Methods","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1002/smtd.202401259","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Memristors and magnetic tunnel junctions are showing great potential in data storage and computing applications. A magnetoelectrically coupled memristor utilizing electron spin and electric field-induced ion migration can facilitate their operation, uncover new phenomena, and expand applications. In this study, devices consisting of Pt/(LaCoO3/SrTiO3)n/LaCoO3/Nb:SrTiO3 (Pt/(LCO/STO)n/LCO/NSTO) are engineered using pulsed laser deposition to form the LCO/STO superlattice layer, with Pt and NSTO serving as the top and bottom electrodes, respectively. The results show that both memristive and magnetoresistive properties can coexist without any compromise in performance, and the values of ROFF/RON and tunnel magnetoresistance (TMR) ratio are both improved by ≈1000% compared to a single-period heterostructure. Notably, the Pt/(LCO/STO)5/LCO/NSTO device demonstrates superior multilevel storage performance, characterized by extended endurance, reliable retention, high ROFF/RON ratio, significant TMR ratio, and fundamental synaptic behaviors. Furthermore, density functional theory (DFT) is employed to calculate the changes in oxygen vacancies, affecting the overall energy bands and magnetic moments in the monolayer and multi-periodic structures. Simulations using the handwritten digit recognition classification achieve the highest accuracy of 94.38%. These attributes suggest that the devices hold considerable promise for application in data storage and neuromorphic computing, offering a platform for high-density neural circuits in intelligent electronic devices.
Small MethodsMaterials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍:
Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques.
With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community.
The online ISSN for Small Methods is 2366-9608.